Method of endpoint detection of plasma etching process using multivariate analysis

ABSTRACT

Described is a method for determining an endpoint of an etch process using optical emission spectroscopy (OES) data as an input. Optical emission spectroscopy (OES) data are acquired by a spectrometer attached to a plasma etch processing tool. The acquired time-evolving spectral data are first filtered and demeaned, and thereafter transformed into transformed spectral data, or trends, using multivariate analysis such as principal components analysis, in which previously calculated principal component weights are used to accomplish the transform. A functional form incorporating multiple trends may be used to more precisely determine the endpoint of an etch process. A method for calculating principal component weights prior to actual etching, based on OES data collected from previous etch processing, is disclosed, which method facilitates rapid calculation of trends and functional forms involving multiple trends, for efficient and accurate in-line determination of etch process endpoint.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of and claims priority to co-pendingU.S. Nonprovisional patent application Ser. No. 14/056,059, entitled“METHOD OF ENDPOINT DETECTION OF PLASMA ETCHING PROCESS USINGMULTIVARIATE ANALYSIS” filed on Oct. 17, 2013, which is based on andclaims priority to U.S. Provisional Patent Application No. 61/715,047,entitled “METHOD OF ENDPOINT DETECTION OF PLASMA ETCHING PROCESS USINGMULTIVARIATE ANALYSIS” filed on Oct. 17, 2012, all of which applicationsare herein incorporated by reference in their entirety.

BACKGROUND OF THE INVENTION

Field of the Invention

The present invention relates to a method and system for controlling theprocess of etching a structure on a substrate, for example, insemiconductor manufacturing. More particularly, it relates to a methodfor determining an endpoint of an etch process.

Description of Related Art

Plasma etch processes are commonly used in conjunction withphotolithography in the process of manufacturing semiconductor devices,liquid crystal displays (LCDs), light-emitting diodes (LEDs), and somephotovoltaics (PVs). Generally, a layer of radiation-sensitive material,such as photoresist, is first coated on a substrate and exposed topatterned light to impart a latent image thereto. Thereafter, theexposed radiation-sensitive material is developed to remove exposedradiation-sensitive material (or unexposed, if negative tone photoresistis used), leaving a pattern of radiation-sensitive material whichexposes areas to be subsequently etched, and covers areas where noetching is desired. During the etch process, for example a plasma etchprocess, the substrate and radiation-sensitive material pattern areexposed to energetic ions in a plasma processing chamber, so as toeffect removal of the material underlying the radiation-sensitivematerial in order to form etched features, such as vias, trenches, etc.Following etching of the features in the underlying material, theremainder of the radiation-sensitive material is removed from thesubstrate using an ashing or stripping process, to expose formed etchedstructures ready for further processing.

In many types of devices, such as semiconductor devices, the plasma etchprocess is performed in a first material layer overlying a secondmaterial layer, and it is important that the etch process be stoppedaccurately once the etch process has formed an opening or pattern in thefirst material layer, without continuing to etch the underlying secondmaterial layer.

For purposes of controlling the etch process various types of endpointcontrol are utilized, some of which rely on analyzing the chemistry ofthe gas in the plasma processing chamber in order to deduce whether theetch process has progressed, for example, to an underlying layer of adifferent chemical composition than the chemical composition of thelayer being etched. Other processes may rely on direct in-situmeasurements made of structures being etched. In the former group,optical emission spectroscopy (OES) is frequently used to monitor thechemistry of the gas in the plasma processing chamber. The chemicalspecies of the gas in the plasma processing chamber are excited by theplasma excitation mechanism being used, and the excited chemical speciesproduce distinct spectral signatures in the optical emission spectrum ofthe plasma. Changes in the optical emission spectrum due to, forexample, clearing of a layer being etched, and exposing of an underlyinglayer on the substrate, can be monitored and used to precisely end, i.e.endpoint the etch process, so as to avoid etching of the underlyinglayer or formation of other yield defeating defects, such as undercuts,etc.

Depending on the types of structures being etched and the etch processparameters, the change of the optical emission spectrum of the plasma atthe endpoint of the etch process may be very pronounced and easy todetect, or conversely subtle and very difficult to detect. For example,etching of structures with a very low open ratio can make endpointdetection difficult using current algorithms for processing opticalemission spectroscopy (OES) data. Improvements are therefore needed tomake etch endpoint detection based on optical emission spectroscopy(OES) data more robust in such challenging etch process conditions.

SUMMARY OF THE INVENTION

An aspect of the invention is a method for determining etch processendpoint data comprising performing one or more plasma etch process runsin a plasma etch processing tool comprising a spectrometer for acquiringoptical emission spectroscopy (OES) data. During each of the plasma etchprocess runs, optical emission spectroscopy (OES) data sets are sampledat equal time intervals, and optical emission spectroscopy (OES) datamatrices [X] are formed with time samples occupying rows and pixellocations (i.e. wavelengths) occupying columns.

In another aspect of the invention, the acquired optical emissionspectroscopy data matrices [X] are then averaged element by element toform an average optical emission spectroscopy (OES) data matrix[X]^(avg) for the one or more plasma etch process runs. Thereafter, theaverage optical emission spectroscopy (OES) data matrix [X]^(avg) can befiltered to remove noise from the optical emission spectroscopy (OES)data. To improve data quality for further processing, each of theoptical emission spectroscopy (OES) data matrices [X] and the averageoptical emission spectroscopy (OES) data matrix [X]^(avg) are truncatedto remove any portions of the data sets corresponding to plasma startupconditions and any conditions following endpoint of the etch processes.Computations further proceed by calculating a mean optical emissionspectroscopy (OES) data matrix [S_(avg)], in which each element of eachcolumn represents an average of spectrometer pixel intensities over alltime samples retained after truncation, for that spectrometer pixel,i.e. matrix column. The mean optical emission spectroscopy (OES) datamatrix [S^(avg)] is then subtracted from each of the optical emissionspectroscopy (OES) data matrices [X]. The optical emission spectroscopy(OES) data is, therefore, de-meaned. However, unlike what is usuallydone in multivariate analysis, the optical emission spectroscopy (OES)data is not normalized prior to being used as input for multivariateanalysis.

In a further aspect of the invention, the de-meaned and non-normalizedoptical emission spectroscopy (OES) data are now used as an input for aprincipal components analysis (PCA), which transforms the physicaloptical emission spectroscopy (OES) data into a transformed opticalemission spectroscopy (OES) data vector [T]. It also provides aprincipal component weights vector [P] which can be used to subsequentlytransform any physical optical emission spectroscopy (OES) data into theprincipal components domain.

In yet another aspect of the invention, to reliably determine anendpoint of an etch process, the elements of the transformed opticalemission spectroscopy (OES) data vector [T] can be combined into afunctional form f(T_(i)), also called a trend variable, whichparticularly emphasizes the changes that occur to the transformedoptical emission spectroscopy (OES) data vector [T] elements during thetime when the etch process reaches an endpoint. In one embodiment, thetrend variable f(T_(i)) may simply comprise a single element of thetransformed optical emission spectroscopy (OES) data vector [T]. Inother embodiments, the trend variable f(Ti) may include a ratio of twoelements of the transformed optical emission spectroscopy (OES) datavector [T]. The ratio itself may be raised to an integer or non-integerpower. For a further increase of endpoint detection reliability, theelements of the transformed optical emission spectroscopy (OES) datavector [T] can be shifted by subtracting a minimum value, or multiple ofthe minimum value of each element of the transformed optical emissionspectroscopy (OES) data vector [T] evaluated for all sample times duringan etch process. This shifting, or removal of a “pedestal” from theelements of the transformed optical emission spectroscopy (OES) datavector [T] further assists in rendering the method more sensitive tosubtle changes of plasma chemistry associated with certain etchprocesses. In one embodiment, the functional form of the trend variablemay be f(T_(i))=(T₂−2·min(T₂))²/(T₃−2·min(T₃))², involving the square ofthe ratio of elements T₂ and T₃ of the transformed optical emissionspectroscopy (OES) data vector [T], each element being shifted by twicethe minimum value of each of the respective elements.

In a further aspect of the invention, the values of the principalcomponent weights vector [P], the mean optical emission spectroscopy(OES) data matrix [S_(avg)], and optionally the minimum valuesmin(T_(i)) of the elements of the transformed optical emissionspectroscopy (OES) data vector [T] can be saved on volatile ornon-volatile data storage media for use in in-situ endpoint detection ofnominally same or similar etch processes.

In an aspect of the invention, the process of in-situ endpoint detectionof an etch process proceeds by retrieving previously stored values ofthe principal component weights vector [P], the mean optical emissionspectroscopy (OES) data matrix [S^(avg)], and optionally the minimumvalues min(T_(i)) of the elements of the transformed optical emissionspectroscopy (OES) data vector [T], from the data storage media. Uponloading of a substrate into the plasma etch processing chamber, andinitiating a plasma, measurements of optical emission spectroscopy (OES)data are taken using the spectrometer mounted on the plasma etchprocessing tool at regular or irregular intervals during the etchprocess. Acquired optical emission spectroscopy (OES) data aremultiplied by the principal component weights vector [P] after havingthe mean optical emission spectroscopy (OES) data matrix [S^(avg)]subtracted, for rapid transformation of in-situ acquired data into theprincipal components domain. Once transformed, the calculated elementsof the transformed optical emission spectroscopy (OES) data vector [T]can be combined in a pre-selected functional form f(T_(i)), or trendvariable, as described before, whose evolution in time allows a precisein-situ determination of an endpoint of the etch process. In anembodiment, the functional form f(T_(i)), or the trend variable, mayinvolve the use of shifted values of the elements of the transformedoptical emission spectroscopy (OES) data vector [T], the shifting ofwhich is accomplished by subtracting the minimum values min(T_(i)) ofthe elements of the transformed optical emission spectroscopy (OES) datavector [T].

BRIEF DESCRIPTION OF THE DRAWINGS

A more complete appreciation of the invention and many of the attendantadvantages thereof will become readily apparent with reference to thefollowing detailed description, particularly when considered inconjunction with the accompanying drawings, in which:

FIG. 1 is a schematic of an exemplary plasma etch processing system witha light detection device including a spectrometer used for acquisitionof optical emission spectroscopy (OES) data, and a controllerimplementing the etch endpoint detection method described herein.

FIG. 2 is a flowchart of the method of preparing etch endpoint data forlater in-situ etch endpoint detection.

FIG. 3 is a flowchart of the method of in-situ etch endpoint detection.

FIGS. 4A-D shows exemplary graphs of the time evolution of the firstfour elements of a transformed optical emission spectroscopy (OES) datavector [T].

FIG. 5 shows an exemplary graph of a time evolution of a trend variablefunctional form involving a ratio of shifted elements of the transformedoptical emission spectroscopy (OES) data vector [T].

DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS

In the following description, in order to facilitate a thoroughunderstanding of the invention and for purposes of explanation and notlimitation, specific details are set forth, such as particulargeometries of a lithography, coater/developer, and gap-fill treatmentsystem, and descriptions of various components and processes. However,it should be understood that the invention may be practiced in otherembodiments that depart from these specific details.

In the description to follow, the terms radiation-sensitive material andphotoresist may be used interchangeably, photoresist being only one ofmany suitable radiation-sensitive materials for use in photolithography.Similarly, hereinafter the term substrate, which represents theworkpiece being processed, may be used interchangeably with terms suchas semiconductor wafer, LCD panel, light-emitting diode (LED),photovoltaic (PV) device panel, etc., the processing of all of whichfalls within the scope of the claimed invention.

Reference throughout this specification to “one embodiment” or “anembodiment” means that a particular feature, structure, material, orcharacteristic described in connection with the embodiment is includedin at least one embodiment of the invention, but do not denote that theyare present in every embodiment. Thus, the appearances of the phrases“in one embodiment” or “in an embodiment” in various places throughoutthis specification are not necessarily referring to the same embodimentof the invention. Furthermore, the particular features, structures,materials, or characteristics may be combined in any suitable manner inone or more embodiments.

Various operations will be described as multiple discrete operations inturn, in a manner that is most helpful in understanding the invention.However, the order of description should not be construed as to implythat these operations are necessarily order dependent. In particular,these operations need not be performed in the order of presentation.Operations described may be performed in a different order than thedescribed embodiment. Various additional operations may be performedand/or described operations may be omitted in additional embodiments.

According to an embodiment of the present invention, depicted in FIG. 1is a plasma etch processing system 10 and a controller 55, wherein thecontroller 55 is coupled to plasma etch processing system 10. Controller55 is configured to monitor the performance of plasma etch processingsystem 10 using data obtained from a variety of sensors disposed in theplasma etch processing system 10. For example, controller 55 can be usedto control various components of plasma etch processing system 10, todetect faults, and to detect an endpoint of an etch process.

According to the illustrated embodiment of the present inventiondepicted in FIG. 1, the plasma etch processing system 10 includes aprocess chamber 15, substrate holder 20, upon which a substrate 25 to beprocessed is affixed, gas injection system 40, and vacuum pumping system58. Substrate 25 can be, for example, a semiconductor substrate, awafer, or a liquid crystal display (LCD). The plasma etch processingsystem 10 can be, for example, configured to facilitate the generationof plasma in processing region 45 adjacent a surface of substrate 25,where plasma is formed via collisions between heated electrons and anionizable gas. An ionizable gas or mixture of gases is introduced viagas injection system 40, and the process pressure is adjusted.Desirably, plasma is utilized to create materials specific to apredetermined materials process, and to aid the removal of material fromthe exposed surfaces of substrate 25. For example, controller 55 can beused to control vacuum pumping system 58 and gas injection system 40.

Substrate 25 can be, for example, transferred into and out of plasmaetch processing system 10 through a slot valve (not shown) and chamberfeed-through (not shown) via robotic substrate transfer system where itis received by substrate lift pins (not shown) housed within substrateholder 20 and mechanically translated by devices housed therein. Oncesubstrate 25 is received from substrate transfer system, it is loweredto an upper surface of substrate holder 20.

For example, substrate 25 can be affixed to the substrate holder 20 viaan electrostatic clamping system 28. Furthermore, substrate holder 20can further include a cooling system including a re-circulating coolantflow that receives heat from substrate holder 20 and transfers heat to aheat exchanger system (not shown), or when heating, transfers heat fromthe heat exchanger system. Moreover, gas can be delivered to theback-side of the substrate via a backside gas delivery system 26 toimprove the gas-gap thermal conductance between substrate 25 andsubstrate holder 20. Such a system can be utilized when temperaturecontrol of the substrate is required at elevated or reducedtemperatures. For example, temperature control of the substrate can beuseful at temperatures in excess of the steady-state temperatureachieved due to a balance of the heat flux delivered to the substrate 25from the plasma and the heat flux removed from substrate 25 byconduction to the substrate holder 20. In other embodiments, heatingelements, such as resistive heating elements, or thermo-electricheaters/coolers can be included.

With continuing reference to FIG. 1, process gas can be, for example,introduced to processing region 45 through gas injection system 40.Process gas can, for example, include a mixture of gases such as argon,CF₄ and O₂, or Ar, C₄F₈ and O₂ for oxide etch applications, or otherchemistries such as, for example, O₂/CO/Ar/C₄F₈, O₂/CO/Ar/C₅F₈,O₂/CO/Ar/C₄F₆, O₂/Ar/C₄F₆, N₂/H₂. Gas injection system 40 includes ashowerhead, where process gas is supplied from a gas delivery system(not shown) to the processing region 45 through a gas injection plenum(not shown) and a multi-orifice showerhead gas injection plate (notshown).

Vacuum pumping system 58 can, for example, include a turbo-molecularvacuum pump (TMP) capable of a pumping speed up to 5000 liters persecond (and greater) and a gate valve for throttling the chamberpressure. In conventional plasma processing devices utilized for dryplasma etch, a 1000 to 3000 liter per second TMP is generally employed.TMPs are useful for low pressure processing, typically less than 50mTorr. At higher pressures, the TMP pumping speed falls offdramatically. For high pressure processing (i.e., greater than 100mTorr), a mechanical booster pump and dry roughing pump can be used.Furthermore, a device for monitoring chamber pressure (not shown) iscoupled to the process chamber 15. The pressure measuring device can be,for example, a Type 628B Baratron absolute capacitance manometercommercially available from MKS Instruments, Inc. (Andover, Mass.).

As further shown in FIG. 1, the plasma etch processing system 10,includes a plasma source 80. For example, RF or microwave power can becoupled from generator 82 through impedance match network or tuner 84 tothe plasma source 80. A frequency for the application of RF power to theplasma source ranges from 10 MHz to 200 MHz and is preferably 60 MHz,for capacitively-coupled, (CCP), inductively-coupled (ICP), andtransformer-coupled (TCP) plasma sources. For microwave plasmasources80, such as electron cyclotron (ECR) and surface wave plasma (SWP)sources, typical frequencies of operation of generator 82 are between 1and 5 GHz, and preferably about 2.45 GHz. An example of a surface waveplasma (SWP) source 80 is a radial line slotted antenna (RLSA) plasmasource. Moreover, controller 55 can be coupled to generator 82 andimpedance match network or tuner 84 in order to control the applicationof RF or microwave power to plasma source 80.

As shown in FIG. 1, substrate holder 20 can be electrically biased at anRF voltage via the transmission of RF power from RF generator 30 throughimpedance match network 32 to substrate holder 20. The RF bias can serveto attract ions from the plasma formed in processing region 45, tofacilitate the etch process. The frequency for the application of powerto the substrate holder 20 can range from 0.1 MHz to 30 MHz and ispreferably 2 MHz. Alternately, RF power can be applied to the substrateholder 20 at multiple frequencies. Furthermore, impedance match network32 serves to maximize the transfer of RF power to plasma in processchamber 15 by minimizing the reflected power. Various match networktopologies (e.g., L-type, π-type, T-type, etc.) and automatic controlmethods can be utilized.

Various sensors are configured to receive tool data from plasma etchprocessing system 10. The sensors can include both sensors that areintrinsic to the plasma etch processing system 10 and sensors extrinsicto the plasma etch processing system 10. Intrinsic sensors can includethose sensors pertaining to the functionality of plasma etch processingsystem 10 such as the measurement of the Helium backside gas pressure,Helium backside flow, electrostatic chuck (ESC) voltage, ESC current,substrate holder 20 temperature (or lower electrode (LEL) temperature),coolant temperature, upper electrode (UEL) temperature, forward RFpower, reflected RF power, RF self-induced DC bias, RF peak-to-peakvoltage, chamber wall temperature, process gas flow rates, process gaspartial pressures, chamber pressure, capacitor settings (i.e., C1 and C2positions), a focus ring thickness, RF hours, focus ring RF hours, andany statistic thereof. Alternatively, extrinsic sensors can includethose not directly related to the functionality of plasma etchprocessing system 10 such as a light detection device 34 for monitoringthe light emitted from the plasma in processing region 45 as shown inFIG. 1.

The light detection device 34 can include a detector such as a (silicon)photodiode or a photomultiplier tube (PMT) for measuring the total lightintensity emitted from the plasma. The light detection device 34 canfurther include an optical filter such as a narrow-band interferencefilter. In an alternate embodiment, the light detection device 34includes a line CCD (charge coupled device) or CID (charge injectiondevice) array and a light dispersing device such as a grating or aprism. Additionally, light detection device 34 can include amonochromator (e.g., grating/detector system) for measuring light at agiven wavelength, or a spectrometer (e.g., with a rotating or fixedgrating) for measuring the light spectrum. The light detection device 34can include a high resolution optical emission spectroscopy (OES) sensorfrom Peak Sensor Systems. Such an OES sensor has a broad spectrum thatspans the ultraviolet (UV), visible (VIS) and near infrared (NIR) lightspectrums. In the Peak Sensor System, the resolution is approximately1.4 Angstroms, that is, the sensor is capable of collecting 5550wavelengths from 240 to 1000 nm. In the Peak System Sensor, the sensoris equipped with high sensitivity miniature fiber optic UV-VIS-NIRspectrometers which are, in turn, integrated with 2048 pixel linear CCDarrays.

The spectrometers in one embodiment of the present invention receivelight transmitted through single and bundled optical fibers, where thelight output from the optical fibers is dispersed across the line CCDarray using a fixed grating. Similar to the configuration describedabove, light emitting through an optical vacuum window is focused ontothe input end of the optical fibers via a convex spherical lens. Threespectrometers, each specifically tuned for a given spectral range (UV,VIS and NIR), form a sensor for a process chamber. Each spectrometerincludes an independent A/D converter. And lastly, depending upon thesensor utilization, a full emission spectrum can be recorded every 0.01to 1.0 seconds.

Alternatively, in an embodiment, a spectrometer with all reflectiveoptics may be employed by light detection device 34. Furthermore, in anembodiment, a single spectrometer involving a single grating and asingle detector for the entire range of light wavelengths being detectedmay be used. The design and use of optical emission spectroscopyhardware for acquiring optical emission spectroscopy (OES) data usinge.g. light detection device 34, are well known to those skilled in theart of optical plasma diagnostics.

Controller 55 includes a microprocessor, memory, and a digital I/O port(potentially including D/A and/or A/D converters) capable of generatingcontrol voltages sufficient to communicate and activate inputs to plasmaetch processing system 10 as well as monitor outputs from plasma etchprocessing system 10. As shown in FIG. 1, controller 55 can be coupledto and exchange information with RF generator 30, impedance matchnetwork 32, gas injection system 40, vacuum pumping system 58, backsidegas delivery system 26, electrostatic clamping system 28, and lightdetection device 34. A program stored in the memory is utilized tointeract with the aforementioned components of a plasma etch processingsystem 10 according to a stored process recipe. One example ofcontroller 55 is a DELL PRECISION WORKSTATION 530™, available from DellCorporation, Austin, Tex. Controller 55 can be locally located relativeto the plasma etch processing system 10, or it can be remotely locatedrelative to the plasma etch processing system 10. For example,controller 55 can exchange data with plasma etch processing system 10using at least one of a direct connection, an intranet, and theinternet. Controller 55 can be coupled to an intranet at, for example, acustomer site (i.e., a device maker, etc.), or it can be coupled to anintranet at, for example, a vendor site (i.e., an equipmentmanufacturer). Additionally, for example, controller 55 can be coupledto the internet. Furthermore, another computer (i.e., controller,server, etc.) can, for example, access controller 55 to exchange datavia at least one of a direct connection, an intranet, and the internet.The controller 55 also implements an algorithm for detection of anendpoint of an etch process being performed in plasma etch processingsystem 10, based on input data provided from light detection device 34,as described further herein.

The process of endpoint determination in accordance with an embodimentof the invention proceeds in two phases. In the first phase, opticalemission spectroscopy (OES) data are acquired using light detectiondevice 34 during one or more etch processing runs performed in a plasmaetch processing system 10, such that a multivariate model can beestablished of the acquired optical emission spectroscopy (OES) data.Once the multivariate model of the optical emission spectroscopy (OES)data has been established, it can be used in a second phase for in-situetch endpoint detection, as long as the etch process being run duringthe second phase is reasonably similar in terms of structures beingetched, etch process conditions, etch processing system used, etc., tothose used in the one or more etch processing runs performed in thefirst phase. This is to ensure the validity of multivariate model.

With reference now to FIG. 2, where a flowchart 200 of the first phaseis shown, the process of setting up a multivariate model of the opticalemission spectroscopy (OES) data begins at step 210 by performing a setof one or more plasma etch process runs. As mentioned before, the etchprocess conditions during these runs need to be reasonably close to theetch processes whose endpoint will be determined in the second phase,for the validity of the multivariate model to be maintained. Duringthese plasma etch process runs, optical emission spectroscopy (OES) datais acquired using, for example, light detection device 34 of plasma etchprocessing system 10. During each plasma etch process run, spectra areacquired n times, where n is an integer greater than 1. The samplinginterval between successive optical emission spectroscopy (OES) dataacquisitions, i.e. spectra acquisitions, may vary from 0.01 to 1.0seconds. Each acquired optical emission spectroscopy (OES) data set,i.e. spectrum, contains m measured light intensities corresponding tothe m pixels of a CCD (charge coupled device) detector, each pixelcorresponding to a certain light wavelength projected upon the pixel bya diffraction grating which is typically employed as a light dispersiondevice in light detection device 34. CCD detectors may have from 256 to8192 pixels, depending on the desired spectral resolution, but pixelnumbers of 2048 or 4096 are most commonly used.

The process continues in step 215 where optical emission spectroscopy(OES) data matrices [X]^([i]) are set up for all plasma etch processruns i=1, 2, . . . k. Each matrix [X]^([i]) is a n×m matrix, whereacquired spectra are arranged in rows of the matrix, such that the rowscorrespond to n instants in time when optical emission spectroscopy(OES) data are taken, and columns correspond to the pixel number m.

In step 220, an n×m average optical emission spectroscopy (OES) datamatrix [X^(avg)] is calculated by averaging each element of all acquiredmatrices [X]^([i]) over all i=1, 2, . . . k plasma etch process runs.

In step 225, noise is filtered from the average optical emissionspectroscopy (OES) data matrix [X^(avg)]. Various types of filters canbe used, such as, for example, the moving average filter. Furthermore,different parameters may be chosen by the operator for the chosenfilter, depending on the amount of noise encountered in the data, whichmay correlate to a plasma etch processing system being used, structuresbeing etched, the etch process conditions being used, etc. For example,in the case of the moving average filter, the filter window may beadjusted to the most appropriate width so noise is effectively removed;yet important signal data is retained. The inventors have discoveredthat better results can be obtained by filtering the data at this stage,rather than after constructing a multivariate model of the acquiredoptical emission spectroscopy (OES) data, as is customarily done inprior art optical emission spectroscopy (OES) etch endpoint systems.

In step 230, all acquired optical emission spectroscopy (OES) datamatrices [X]^([i]) are truncated to remove spectra acquired duringplasma startup and optionally following actual etch process endpoint. Bytruncating the data, matrices [X]^([i]) are cleaned of any data thatdoes not pertain to the stable period of etching ensuing once the plasmahas stabilized in the plasma etch processing system 10. Sincemeasurements made at certain instants of time are truncated, rows ofmatrices [X]^([i]) are typically removed. Optionally, certain wavelengthranges can also be truncated if the plasma emission wavelengths in thetruncated portions of the spectra do not contribute to the etch endpointsignal. At this time, the average optical emission spectroscopy (OES)data matrix [X^(avg)] may also be truncated in the same fashion asmatrices [X]^([i]).

In step 235, a mean optical emission spectroscopy (OES) data matrix[S^(avg)] is computed, wherein all elements of each column are set tothe average across the entire column (i.e. across all instants in time)of the elements of the average optical emission spectroscopy (OES) datamatrix [X^(avg)]. This matrix [S^(avg)] is used for de-meaning of alloptical emission spectroscopy (OES) data.

In step 240, the mean optical emission spectroscopy (OES) data matrix[S^(avg)] is subtracted from each acquired optical emission spectroscopy(OES) data matrix [X]^([i]), i=1, 2, . . . k, to perform the step ofde-meaning, i.e. average subtraction, prior to constructing amultivariate model of the acquired optical emission spectroscopy (OES)data. In prior art optical emission spectroscopy (OES) etch endpointsystems, beside de-meaning, the optical emission spectroscopy (OES) datais also always normalized using, for example, the standard deviation ofthe optical emission spectroscopy (OES) data. However, just like in thecase of data filtering, as previously discussed, inventors havediscovered that normalization, as done in the prior art, leads to lessreliable endpoint detection, particularly under challenging detectionconditions. Therefore, the data are kept non-normalized.

In step 245, the de-meaned optical emission spectroscopy (OES) data[X]^([i])−[S^(avg)] are used as input into a multivariate analysis, suchas for example, principal components analysis (PCA). A principalcomponents (PC) model[T]=([X] ^([i]) −[S ^(avg)])[P]  (Eq. 1)

is set up, wherein the vector [T] represents the transformed opticalemission spectroscopy (OES) data vector. The vector T has elements Ti,called principal components, which represent a reduced set of variableswith which the input data, in this case optical emission spectroscopy(OES) data, can be described. The vector [P] is a vector of principalcomponents (PC) weights, which can be used to transform de-meanedoptical emission spectroscopy (OES) data into a transformed opticalemission spectroscopy (OES) data vector [T], in accordance with Eq. 1.The methods of setting up and creating a principal components analysis(PCA) model are well known to persons skilled in the art.

Since the goal of the first phase is to pre-calculate usefulmultivariate model parameters for later in-situ etch endpoint detection,various parameters are now saved for later use. In step 250, the meanoptical emission spectroscopy (OES) data matrix [S^(avg)] is saved tovolatile or non-volatile storage media, to facilitate de-meaning ofin-situ measured optical emission spectroscopy (OES) data. Also in thisstep, the vector [P] of principal components (PC) weights is saved tovolatile or non-volatile storage media to facilitate rapidtransformation of in-situ measured optical emission spectroscopy (OES)data into a transformed optical emission spectroscopy (OES) data vector[T].

In some case, inventors have discovered that it is useful for endpointdetection reliability to shift the calculated values of elements T_(i)of the transformed optical emission spectroscopy (OES) data vector [T],i.e. the principal components, as they evolve over time, such that theyconcentrate around the value of zero, rather than grow to large positiveor negative values. This shifting is accomplished in step 255, where atleast one element T_(i) of the transformed optical emission spectroscopy(OES) data vector [T] is evaluated for each instant in time during theetch process when measurements were taken, and a minimum value of suchelement, or elements, min(Ti), are found. For this purpose,time-evolving data from the average optical emission spectroscopy (OES)data matrix [X^(avg)], or other data, may be used. This minimum value isthen stored in step 260 on volatile or non-volatile storage media forlater use in in-situ endpoint detection, whereby the minimum valuemin(T_(i)) of an element T_(i) of the transformed optical emissionspectroscopy (OES) data vector [T] can be used to shift thetime-evolving values of the same element T_(i) of the transformedoptical emission spectroscopy (OES) data vector [T], calculated fromin-situ measured optical emission spectroscopy (OES) data.

The stored data values on volatile or non-volatile storage media are nowready to be used in the second phase, i.e. in in-situ etch endpointdetection. The entire process outlined in flowchart 200 of FIG. 2 can beexecuted in controller 55 of plasma etch processing system 10 of FIG. 1.

FIG. 3 shows a flowchart 300 of the process of in-situ endpointdetection in a plasma etch processing system 100, equipped with lightdetection device 34, having available the data saved in steps 250 and260 of flowchart 200.

In steps 310 and 315, the previously determined mean optical emissionspectroscopy (OES) data matrix [S^(avg)] and the vector [P] of principalcomponents (PC) weights are retrieved from volatile or non-volatilestorage media and loaded into memory of controller 55 of plasma etchprocessing system 10 of FIG. 1. Controller 55 will perform all thein-situ calculations needed to determine endpoint of a plasma process.Also, if used, at least one minimum value min(T_(i)) of an element T_(i)of the transformed optical emission spectroscopy (OES) data vector [T]can be loaded from volatile or non-volatile media into memory ofcontroller 55, in step 320.

In step 325, a substrate 25 is loaded into plasma etch processing system10 and a plasma is formed in processing region 45.

In step 330, light detection device 34 is now used to acquire opticalemission spectroscopy (OES) data in-situ, i.e. during the etch processevolving over time.

In step 335, the retrieved mean optical emission spectroscopy (OES) datamatrix [S^(avg)] elements are subtracted from each acquired opticalemission spectroscopy (OES) data set, i.e. spectrum, to de-mean theacquired spectra prior to transformation using the already developedmultivariate model. As was previously mentioned, inventors havediscovered that the endpoint detection process is more robust ifnormalization of data prior to transformation is not done, so hence itis not done at this step, just as it was not done during the firstphase.

In step 340, the already developed the principal components analysis(PCA) multivariate model is used to transform the de-meaned opticalemission spectroscopy (OES) data into a transformed optical emissionspectroscopy (OES) data vector [T], i.e. the principal components, usingEq. 1 and the retrieved vector [P] of principal components (PC) weights.This process is very fast because it involves only a simplemultiplication, and is thus amenable to in-situ real-time calculation.The computed elements T_(i) of transformed optical emission spectroscopy(OES) data vector [T], as they evolve over time, can be used forendpoint detection.

FIGS. 4A-D show time evolution of elements T₁ through T₄ of thetransformed optical emission spectroscopy (OES) data vector [T], i.e.the first four principal components, for an etch process in which theopen ratio has a low value of 0.06%—a very challenging condition forendpoint detection using optical emission spectroscopy (OES). From FIG.4A, one can see that the first principal component T₁, despite carryingstatistically most information about the optical emission spectroscopy(OES) data, does not show a discernible change in the vicinity of theetch endpoint (located at slightly more than 30 seconds, in all graphs).FIG. 4B shows that second principal component T₂ does show a discernibleminimum, or dip 410, at the endpoint, but that dip 410 is comparable toother minima in the time evolution of T₂, so principal component T₂ isnot very useful for endpoint detection, either, under these conditions.FIG. 4C shows that the third principal component T₃ does show amarginally useful minimum or dip 420 at the etch endpoint, and this canbe used for endpoint detection, but it is questionable whether it alonecan be used reliably for endpoint detection in case where data isnoisier than shown here. Lastly, FIG. 4D shows the fourth principalcomponent T₄, which like principal component T₂ is not a reliableindicator of endpoint, due to the minimum at endpoint being comparableto other minima. Most prior art optical emission spectroscopy (OES) etchendpoint systems utilize a single principal component T_(i) for endpointdetection.

From the foregoing, it can be seen that a need exists for furtherimprovement of endpoint detection using time-evolving values of elementsT_(i) of the transformed optical emission spectroscopy (OES) data vector[T]. The inventors have discovered that by combining multiple principalcomponents into a functional form f(T_(i)) can lead to better and morereliable endpoint detection. Specifically, the inventors have discoveredthat the time-evolving functional form involving shifted principalcomponents (using twice the minimum value of a principal component as ashifting distance), i.e.f(Ti)=(T ₂−2·min(T ₂))²/(T ₃−2·min(T ₃))²  (Eq. 2)

can be particularly useful for etch endpoint detection when etchconditions such as those in FIGS. 4A-D are used, i.e. low open ratiostructures are etched. The time-evolving signal f(T_(i)) involvingmultiple principal components T_(i) will be hereinafter referred to as atrend variable. Examination of Eq. 2. shows that the trend variablef(Ti) can be readily and efficiently evaluated in-situ, in real time,once principal components T_(i) are computed, further utilizingretrieved minimum values min(T_(i)) of elements T_(i) of the transformedoptical emission spectroscopy (OES) data vector [T]. This computationoccurs in step 345 of flowchart 300.

In step 350, each time-evolving element T_(i) of the transformed opticalemission spectroscopy (OES) data vector [T] can be differentiated tofurther facilitate endpoint detection using trend variable slope data.

FIG. 5 shows a time evolution of trend variable f(T_(i)) of Eq. 2 forthe same etch process in which principal components T₁ through T₄ ofFIGS. 4A-D were obtained. It is very clear from the graph that thefunctional form f(T_(i)) of Eq. 2 is preferred over single principalcomponents T_(i) because of the deep, and thus easily identified minimum510 that the differentiated trend variable f(T_(i)) goes through at etchendpoint.

Inventors have also discovered that other functional forms of the trendvariable f(T_(i)) may be successfully used in less challengingconditions, e.g. T₂/T₃, (T₂/T₃)², (T₂−2·min(T₂))/(T₃−2·min(T₃)), etc.Most of these functional forms involve a ratio of principal components,as opposed to the use of principal components alone, as is done in theprior art, and may employ varying shifting distances to bring theprincipal component values close to zero, so the values of ratios ofprincipal components can be increased for easy endpoint detection.

Now that the time-evolving trend variable f(T_(i)) has been calculated,controller 55 of plasma etch processing system 10 needs to make adecision, in step 355, whether endpoint has been reached. If indeed ithas been reached, the etch process is ended at step 360, otherwise theetch process is continued, and continuously monitored for etch endpointvia steps 330-355 of flowchart 300.

Persons skilled in the relevant art can appreciate that manymodifications and variations are possible in light of the aboveteaching. Persons skilled in the art will recognize various equivalentcombinations and substitutions for various components shown in thefigures. It is therefore intended that the scope of the invention belimited not by this detailed description, but rather by the claimsappended hereto.

What is claimed is:
 1. A method for in-situ determination of etchprocess endpoint, comprising: providing a mean optical emissionspectroscopy (OES) data matrix [S_(avg)] from multiple historical OESdata matrices each corresponding to a respective historical etch processrun, wherein each historical OES data matrix is an n×m matrix with rowscorresponding to n instants in time when OES data are taken, and columnscorrespond to an intensity pixel number m as measured by an OESdetector, and wherein the mean OES data matrix [S_(avg)] is an n×mmatrix of average values calculated from corresponding OES data fromsaid multiple historical OES data matrices; providing a principalcomponent weights vector [P] from the mean OES data matrix [Savg];loading a substrate into a plasma etch processing tool; igniting aplasma in the plasma etch processing tool to initiate an etch process;acquiring current optical emission spectroscopy (OES) data sets from aspectrometer on the plasma etch processing tool at predetermined timeintervals during the etch process; from each acquired current opticalemission spectroscopy (OES) data set, subtracting the provided meanoptical emission spectroscopy (OES) data matrix [S_(avg)], to de-meaneach acquired current optical emission spectroscopy (OES) data setwithout normalizing the current (OES) data set; transforming eachacquired, de-meaned, and non-normalized current optical emissionspectroscopy (OES) data set into transformed optical emissionspectroscopy (OES) data, by calculating at least one element of atransformed optical emission spectroscopy (OES) data vector [T] usingthe provided principal component weights vector [P]; from the calculatedat least one element of the transformed optical emission spectroscopy(OES) data vector [T], further calculating a trend variable f(Ti) frommultiple principal components; and detecting an endpoint of the etchprocess from the further calculated values of the trend variable f(Ti)during the etch process.
 2. The method of claim 1, further comprising:stopping the etch process upon endpoint detection.
 3. The method ofclaim 1, wherein a functional form of the trend variable f(Ti) is acalculated single element of the transformed optical emissionspectroscopy (OES) data vector [T].
 4. The method of claim 1, wherein afunctional form of the trend variable f(Ti) contains a ratio of twocalculated elements of the transformed optical emission spectroscopy(OES) data vector [T].
 5. The method of claim 1, further comprising:providing a previously calculated and stored minimum value min(Ti) of atleast one element of the transformed optical emission spectroscopy (OES)data vector [T].
 6. The method of claim 5, wherein a functional formf(Ti) of the trend variable f(Ti) is an element of the transformedoptical emission spectroscopy (OES) data vector [T] from which the twicethe minimum value min(Ti) of the same element of the transformed opticalemission spectroscopy (OES) data vector [T] has been subtracted.
 7. Themethod of claim 5, wherein a selected functional form f(Ti) of the trendvariable f(Ti) is a ratio of two elements of the transformed opticalemission spectroscopy (OES) data vector [T], wherein twice the minimumvalues min(Ti) of each of the elements of the transformed opticalemission spectroscopy (OES) data vector [T] have been subtracted fromthe respective elements of the transformed optical emission spectroscopy(OES) data vector [T] prior to computing the ratio.
 8. The method ofclaim 7, wherein the selected functional form f(T_(i)) of the trendvariable f(T_(i)) involves a second (T₂) and third (T₃) element of thetransformed optical emission spectroscopy (OES) data vector [T], and isof the form f(T_(i))=(T₂−2 min(T₂))²/(T₃−2·min(T₃))².
 9. The method ofclaim 1, wherein the step of detecting an endpoint of the etch processcomprises evaluating a differential of the trend variable f(T_(i))during the etch process and detecting the endpoint of the etch processfrom the differentiated trend variable f(T_(i)).